Data Analyst (Pharmaceutical / Life Sciences)

Role Overview

The analyst will collaborate with cross-functional stakeholders to identify opportunities for improvement, develop sustainable digital solutions, and provide data-driven insights that enhance performance and decision-making.

• Develop and implement digital solutions aligned with stakeholder requirements using appropriate platforms and tools.
• Conduct User Acceptance Testing (UAT) to ensure solutions are efficient, reliable, and user-friendly, incorporating user feedback to improve system functionality and performance.
• Collaborate with IT, Business Excellence, and other internal teams to design and enhance systems for data collection, storage, and analysis.
• Create clear documentation and troubleshooting guides to ensure the long-term sustainability of implemented digital tools.
• Perform ad-hoc and exploratory data analyses to address complex business challenges and support ongoing strategic initiatives.
• Identify and interpret key trends from laboratory and process data to support data-driven decision-making.
• Ensure compliance with data governance standards, maintaining consistency in data definitions, sources, and quality.
• Design and optimize data extraction processes to consolidate and standardize information from multiple systems.
• Communicate regularly with management and stakeholders to gather requirements, provide progress updates, and present analytical findings.
• Deliver user training and knowledge transfer sessions to ensure smooth adoption and effective use of digital systems.

Requirements:

• Bachelor’s degree in engineering, Computer Science, Statistics, or any relevant discipline.
• Certification in business data analysis or a related area is an advantage.
• 3–6 years of experience in data analytics, digital transformation, or business analysis within the pharmaceutical or life sciences sector.
• Proficiency in data and digital tools including Microsoft Power Platform (Power BI, PowerApps, Power Automate), Smartsheet, SQL, and Python.
• Proven experience in developing dashboards, reports, and analytics solutions that enhance operational efficiency.
• Strong analytical thinking, data interpretation, and problem-solving abilities.
• Knowledge or experience in BIO manufacturing processes, IT/OT systems, and GxP-compliant environments is preferred.
• Familiarity with data governance principles and basic machine learning applications is beneficial.